A Group-Based Dynamic Neighbor Discovery Algorithm in Mobile Sensor Networks

At present, wireless sensor networks are more and more favored by experts and scholars, and become a research hotspot in the field of sensing. Sensor networks are mainly used in environmental monitoring, wildlife detection and so on. When a sensor node is in a fast-moving environment, the node needs to discover its neighbors as quickly as possible. Therefore, neighbor discovery has attracted the attention of researchers. Neighbor discovery is an indispensable process in wireless sensor networks. Most of the current neighbor discovery designs are based on paired discovery and a fixed duty cycle. Only when two nodes wake up at the same time can they discover each other. This is completely passive neighbor discovery, and the network discovery delay is too large. And the nodes in the network are constantly moving. This is a challenging problem to reduce the discovery delay. This paper proposes a neighbor discovery algorithm (GDA, in short) that dynamically adjusts the wake-up time of nodes based on group spatial characteristics. At the same time, in order to effectively balance the relationship between energy consumption and discovery delay, a neighbor discovery algorithm that can selectively recommend method of neighbor nodes. This method can recommend suitable neighbor nodes and improve the early detection time. This paper elaborates the network model and algorithm implementation in detail. A large number of simulation results show that the algorithm has achieved good results in reducing discovery delay and network energy consumption.